
import torch as t
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.activation import Sigmoid


class BlackUpsample(nn.Module):
    
    def __init__(self, inplane, outplane):
        super(BlackUpsample, self).__init__()
        
        self.model = nn.Sequential(
            nn.Upsample(scale_factor=2, mode='bilinear',align_corners=False),
            nn.Conv2d(inplane, outplane, (3, 3), stride=1, padding=1, bias=False),
            nn.BatchNorm2d(outplane),
            nn.ReLU(inplace=True),
        )
        
    def forward(self, x):
        return self.model(x)